Data Engineer, Mid

Booz Allen Hamilton•Arlington, VA

8d•$62,000 - $141,000

About The Position

As a Data Engineer, you will support Department of the Air Force data, analytics, and AI missions. You will build and maintain pipelines that acquire, transform, validate, and deliver data across cloud and on-premises environments. In collaboration with mission experts, architects, data scientists, and cybersecurity professionals, you will turn disparate operational data into trusted, reusable assets. You will contribute to production systems through coding, integration, deployment, monitoring, and troubleshooting. Your work will help analysts and AI applications access current, understandable, and appropriately protected data.

Requirements

At least 3 years of experience in data engineering, including building and operating production data pipelines for DoW/DoD missions.
Experience using Python and SQL to integrate data from enterprise databases, APIs, and operational systems.
Experience building automated batch or streaming pipelines with data validation, failure recovery, and performance monitoring.
Experience implementing cloud data infrastructure, including storage, data modeling, and query optimization.
Secret clearance.
Bachelor’s degree in Computer Science, Engineering, Information Systems, or a technology field.

Nice To Haves

Experience with distributed data processing, change data capture, or event-driven architectures.
Experience implementing data catalogs, lineage, semantic models, or governed data products.
Experience engineering datasets and pipelines for machine learning or RAG applications.

Responsibilities

Build and maintain pipelines to acquire, transform, validate, and deliver data across cloud and on-premises environments.
Integrate data from enterprise databases, APIs, and operational systems.
Build automated batch or streaming pipelines with data validation, failure recovery, and performance monitoring.
Implement cloud data infrastructure, including storage, data modeling, and query optimization.
Contribute to production systems through coding, integration, deployment, monitoring, and troubleshooting.
Collaborate with mission experts, architects, data scientists, and cybersecurity professionals to turn operational data into trusted, reusable assets.